Creating a data frame in R from list data that is missing some values

I have a CSV with a long list of data that looks like this:

Date    user_id    value
4/1       1           5
4/1       2           3
4/1       3           10
4/2       1           1
4/2       3           7

and I want to move it into a data frame开发者_JAVA百科 that just has one column of user id's and a column for each date. I'm assuming there is a way to do with with sapply or lapply but I'm not sure how to handle that the user id's don't always exist for every date.

Maybe something using reshape like the following, which assumes your data are stored in dat:

reshape(dat,v.names = "value",idvar = "user_id",
        direction = "wide",timevar = "Date")

  user_id value.4/1 value.4/2
1       1         5         1
2       2         3        NA
3       3        10         7

Or perhaps more simply, use dcast from reshape2:

dcast(dat,user_id~Date)

  user_id 4/1 4/2
1       1   5   1
2       2   3  NA
3       3  10   7

This is also something that tidyr::spread does quite conveniently

require(tidyr)
require(dplyr)

df <- data.frame("Date" = rep(c("Nov", "Dec"), each = 3), 
             "user.id" = rep(1:3, 2),
             "value" = rnorm(6))

df.2 <- df %>% 
spread(Date, value)

df.2
  user.id        Dec       Nov
     1      -1.9094765   -1.101037
     2       0.2358694   -1.418151
     3      -0.4297790   -1.426573